The Alivia Technology Blog

How to Detect Questionable Transactions Through Big Data

In normal circumstances, transactions are simply an instance of buying or selling something; a business deal that is agreed upon by all necessary parties. An easy way to think of legitimate transactions is to view them as being solid or having mass.

However, risky or questionable transactions also occur. Risky transactions are absent of some critical components which makes them less solid and thus have less mass. A risk bearing transaction may lack an approval, not comply with the business rules, or contain conflicting information – all of these conditions indicate a level of risk. This absence of one or more procedural safeguards makes the transaction different than complete and duly authorized transactions; and by our definition, less substantial.

Fraudulent transactions have the least substance. Imagine a legitimate transaction as a golf ball and a fraudulent one as a ping pong ball. The golf ball is going to withstand virtually any level of force, while the ping pong ball will collapse under a modest amount of pressure.

Absolute Insight, through leveraging big data, is designed to isolate and cluster those transactions lacking the proper approvals and safeguards, thus identifying the greatest amount of potential risk. The Absolute Insight engine evaluates all the transactions, scores them and clusters those that appear to lack the proper mass. Once clustered, the engine will bombard them with new and more focused algorithms. The goal is to increase the pressure on these transactions by identifying behavior patterns that defy the normal business environment and increase the level of observation on those transactions providers, or groups of providers.

This will put the results into the hands of skilled auditors and investigators for the final determination of systemic weakness or fraud. Eventually, the fraudulent transactions will – much like a ping pong ball struck with a golf club – implode.